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Abstract: Can implicit feedback substitute for explicit ratings in recommender systems? If so, we could avoid the difficulties associated with gathering explicit ratings from users. How, then, can we capture useful information unobtrusively, and how might we use that information to make recommendations ? In this paper we identify three types of implicit feedback and suggest two strategies for using implicit feedback to make recommendations. Introduction Recommender systems exploit ratings provided by... (Update)
Context of citations to this paper: More
.... by others in similar environments [4] Other behaviors that have been explored include printing, saving, scrolling and bookmarking [6]. The work reported here is an explicit test of the work of [5] in an IR context other than information filtering. Three sources of...
...filtering. User profiles in this case are usually sparse vectors of ratings. A partial solution to this might be to use implicit feedback [11], or methods to increase the density of the dataset. Scalability is a problem because computation grows linearly with the number of...
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BibTeX entry: (Update)
D. Oard and J. Kim. Implicit Feedback for Recommender Systems. In Proceedings of the AAAI Workshop on Recommender Systems, July 1998. http://citeseer.ist.psu.edu/oard98implicit.html More
@misc{ oard98implicit,
author = "D. Oard and J. Kim",
title = "Implicit Feedback for Recommender Systems",
text = "D. Oard and J. Kim. Implicit Feedback for Recommender Systems. In Proceedings
of the AAAI Workshop on Recommender Systems, July 1998.",
year = "1998",
url = "citeseer.ist.psu.edu/oard98implicit.html" }
Citations (may not include all citations):641 The Anatomy of a Large-Scale Hypertextual Web Search Engine - Brin, Page - 1998
155 GroupLens: Applying Collaborative Filtering to Usenet News - Konstan, Miller et al. - 1997
41 Information Filtering Based on User Behavior Analysis and Be.. (context) - Morita, Shinoda - 1994
13 Knowledge-Based Assistance for Accessing Large (context) - Stevens - 1993
10 The State of the Art in Text Filtering (context) - Oard - 1997
4 Read Wear and Edit Wear (context) - Hill, Hollan et al. - 1992
3 and Terry (context) - Goldberg, Nichols et al. - 1992
3 Newsgroup Clustering Based on User Behavior: A Recommendatio.. - Karlgren - 1994
1 Implicit Ratings and Riltering (context) - Nichols - 1997
1 Citation Indexing: Its Theory and Application in Science (context) - Filtering, an et al. - 1979
1 Personalized Navigation for the Web (context) - Modeling, Interaction et al. - 1997
The graph only includes citing articles where the year of publication is known.
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